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尿液生物标志物可预测前列腺癌和活检前的 PI-RADS 评分。

Urine biomarkers can predict prostate cancer and PI-RADS score prior to biopsy.

机构信息

Department of Urology, University Hospital of Zürich, Frauenklinikstrasse 10, 8091, Zürich, Switzerland.

Institute of Tissue Medicine and Pathology, University of Bern, Murtenstrasse 31, 3008, Bern, Switzerland.

出版信息

Sci Rep. 2024 Aug 5;14(1):18148. doi: 10.1038/s41598-024-68026-1.


DOI:10.1038/s41598-024-68026-1
PMID:39103428
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11300834/
Abstract

Prostate-Specific Antigen (PSA) based screening of prostate cancer (PCa) needs refinement. The aim of this study was the identification of urinary biomarkers to predict the Prostate Imaging-Reporting and Data System (PI-RADS) score and the presence of PCa prior to prostate biopsy. Urine samples from patients with elevated PSA were collected prior to prostate biopsy (cohort = 99). The re-analysis of mass spectrometry data from 45 samples was performed to identify urinary biomarkers to predict the PI-RADS score and the presence of PCa. The most promising candidates, i.e. SPARC-like protein 1 (SPARCL1), Lymphatic vessel endothelial hyaluronan receptor 1 (LYVE1), Alpha-1-microglobulin/bikunin precursor (AMBP), keratin 13 (KRT13), cluster of differentiation 99 (CD99) and hornerin (HRNR), were quantified by ELISA and validated in an independent cohort of 54 samples. Various biomarker combinations showed the ability to predict the PI-RADS score (AUC = 0.79). In combination with the PI-RADS score, the biomarkers improve the detection of prostate carcinoma-free men (AUC = 0.89) and of those with clinically significant PCa (AUC = 0.93). We have uncovered the potential of urinary biomarkers for a test that allows a more stringent prioritization of mpMRI use and improves the decision criteria for prostate biopsy, minimizing patient burden by decreasing the number of unnecessary prostate biopsies.

摘要

基于前列腺特异性抗原(PSA)的前列腺癌(PCa)筛查需要进一步完善。本研究旨在寻找尿液生物标志物,以预测前列腺影像报告和数据系统(PI-RADS)评分和前列腺活检前 PCa 的存在。在前列腺活检前收集了 PSA 升高的患者的尿液样本(队列=99)。对 45 个样本的质谱数据分析进行了重新分析,以确定预测 PI-RADS 评分和 PCa 存在的尿液生物标志物。通过 ELISA 对最有前途的候选标志物,即 SPARC 样蛋白 1(SPARCL1)、淋巴管内皮透明质酸受体 1(LYVE1)、α-1-微球蛋白/双体前体(AMBP)、角蛋白 13(KRT13)、分化群 99(CD99)和 hornerin(HRNR)进行定量,并在 54 个样本的独立队列中进行验证。各种生物标志物组合显示出预测 PI-RADS 评分的能力(AUC=0.79)。与 PI-RADS 评分相结合,这些生物标志物可提高前列腺癌阴性男性(AUC=0.89)和具有临床意义的 PCa 男性(AUC=0.93)的检出率。我们发现了尿液生物标志物的潜力,可以进行一项测试,该测试允许更严格地优先考虑 mpMRI 的使用,并改善前列腺活检的决策标准,通过减少不必要的前列腺活检数量,减轻患者的负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/931782bfcf7d/41598_2024_68026_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/5ac4230859a1/41598_2024_68026_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/804a5a6da87d/41598_2024_68026_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/1893ab59ad08/41598_2024_68026_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/bedd35e2db1e/41598_2024_68026_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/6cad60fb3906/41598_2024_68026_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/931782bfcf7d/41598_2024_68026_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/5ac4230859a1/41598_2024_68026_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/804a5a6da87d/41598_2024_68026_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/1893ab59ad08/41598_2024_68026_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/bedd35e2db1e/41598_2024_68026_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/6cad60fb3906/41598_2024_68026_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e38/11300834/931782bfcf7d/41598_2024_68026_Fig6_HTML.jpg

相似文献

[1]
Urine biomarkers can predict prostate cancer and PI-RADS score prior to biopsy.

Sci Rep. 2024-8-5

[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
Urinary Extracellular Vesicle Signatures as Biomarkers in Prostate Cancer Patients.

Int J Mol Sci. 2025-7-18

[2]
Combining Spatial Transcriptomics, Pseudotime, and Machine Learning Enables Discovery of Biomarkers for Prostate Cancer.

Cancer Res. 2025-7-2

本文引用的文献

[1]
Urinary marker panels for aggressive prostate cancer detection.

Sci Rep. 2022-9-1

[2]
Application of Proteogenomics to Urine Analysis towards the Identification of Novel Biomarkers of Prostate Cancer: An Exploratory Study.

Cancers (Basel). 2022-4-15

[3]
Identification of Urine Biomarkers to Improve Eligibility for Prostate Biopsy and Detect High-Grade Prostate Cancer.

Cancers (Basel). 2022-2-23

[4]
Low Levels of Urinary PSA Better Identify Prostate Cancer Patients.

Cancers (Basel). 2021-7-16

[5]
Clinical Utility of 4Kscore, ExosomeDx™ and Magnetic Resonance Imaging for the Early Detection of High Grade Prostate Cancer.

J Urol. 2021-2

[6]
Can the combination of biparametric magnetic resonance imaging and PSA-related indicators predict the prostate biopsy outcome?

Andrologia. 2020-11

[7]
Independent Evaluation of the Respective Predictive Values for High-Grade Prostate Cancer of Clinical Information and RNA Biomarkers after Upfront MRI and Image-Guided Biopsies.

Cancers (Basel). 2020-1-24

[8]
How to make clinical decisions to avoid unnecessary prostate screening in biopsy-naïve men with PI-RADs v2 score ≤ 3?

Int J Clin Oncol. 2019-8-31

[9]
Prostate Health Index outperforms other PSA derivatives in predicting a positive biopsy in men with tPSA <10 ng/mL: Largest prospective cohort in Taiwan.

J Chin Med Assoc. 2019-10

[10]
Combining Prostate Imaging Reporting and Data System, Histogram Analysis, and Prostate-Specific Antigen Density to Determine the Risk of Prostate Cancer in Patients With Prostate-Specific Antigen of 4 to 20 ng/mL.

J Comput Assist Tomogr. 2019

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